Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/wangke19/gemini-ai-helpersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/wangke19/gemini-ai-helpers/issues-by-component)<a href="https://agentmods.dev/commands/wangke19/gemini-ai-helpers/issues-by-component"><img src="https://agentmods.dev/badge/commands/wangke19/gemini-ai-helpers/issues-by-component.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.04904 |
| Opus 5 | $0.00006 | $0.02452 |
| Sonnet 5 | $0.00002 | $0.00981 |
| Haiku 4.5 | $0.00001 | $0.00490 |
Grade B, and why
issues-by-component scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
chmod 600 ~/.jira-credentials Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Solution:** This command uses a secure curl wrapper script that: This is a copy
100% identical to issues-by-component — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 611 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Name
jira:issues-by-component
Synopsis
/jira:issues-by-component <project-key> [time-period] [--component component-name] [--assignee username] [--reporter username] [--status status] [--search search-term] [--search-description]
Description
The jira:issues-by-component command provides a comprehensive view of JIRA issues organized by component. It supports two modes of operation:
- Overview Mode (no
--componentflag): Lists all components with high-level statistics - Detail Mode (
--componentspecified): Shows detailed issue information for a specific component
This command is particularly useful for:
- Understanding component-level workload distribution
- Finding issues by component and user assignment
- Identifying component-specific patterns or problems
- Sprint/release planning by component
- Searching for specific issues within component contexts
- Team capacity planning and workload analysis
Key Features:
- Component organization - Issues grouped by JIRA component
- Flexible time filtering - Filter by creation date or update date
- User filtering - Filter by assignee or reporter
- Status filtering - Focus on specific workflow states
- Text search - Find issues by keywords in summary or description
- Dual-mode output - Overview or detailed views based on your needs
Prerequisites
This command requires JIRA credentials to be configured as environment variables. It uses direct API calls with a secure wrapper script to prevent token exposure.
1. Install the Jira Plugin
If you haven't already installed the Jira plugin, see the Jira Plugin README for installation instructions.
2. Configure JIRA Credentials
Why not use MCP commands? MCP commands have performance issues when fetching large datasets:
- Each MCP response must be processed by Gemini, consuming LLM tokens
- Large result sets (even with pagination) cause 413 errors from Gemini due to tool result size limits
- Processing hundreds of tickets through MCP commands creates excessive context usage
- Direct API calls allow us to stream data to disk without intermediate processing
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 611 lines · 12 tokens per session scan B e9247d841f35
issues-by-component is a command published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 12 tokens to every session and 4,904 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). It is 100% identical to issues-by-component, differing in 10 lines, and is treated as a copy.
Other commands, from other repositories
projects
Provides tools for creating and managing your Supabase projects.
7a_stakeholder_comms
Generate stakeholder-facing communications: release notes, demo scripts, and change briefs.
convert-to-plan
Convert planning artifacts (lite-plan, workflow session, markdown) to issue solutions.
execute
Execute queue with DAG-based parallel orchestration (one commit per solution).
queue
Form execution queue from bound solutions using issue-queue-agent (solution-level).
from-brainstorm
Convert brainstorm session ideas into issue with executable solution for parallel-dev-cycle.